Job Description
- Knowledge of R
- Knowledge of Pandas
- Intermediate English level
- Time and priority management skills
- Communication skills
- Goal development and management
- Prior experience in Banking, Telecommunications, or IT
- Teamwork
- Understand and examine different data sources, platforms, and algorithms
- Develop and maintain statistical models for credit scoring, segmentation, and fraud prevention
- Design various reports tailored to business needs
- Propose solutions adapted to internal and/or external client needs
- Execute standardized processes and propose new standards for the area
- Work with users to identify data needs and delivery mechanisms
- Degree in Financial Engineering, Statistics, Mathematics, Economics, or Systems Engineering
- Over 3 years of experience in Analytics and/or Business Intelligence
- Proficiency in Python, Spark, and SQL
- Diversity, Equity, and Inclusion (DEI)
- Work-life balance
- Professional development
- Authenticity
- Engagement
- Collaboration
- Well-being
- Reward and recognition
- Volunteering
Job Description
An Analytics Data Modeler interprets data and converts it into information to offer ways to improve a business based on business decisions. Factory analysts collect information from various sources and interpret patterns and trends. Once the data is processed, the person must be able to report their results with the highest possible quality and understanding to different units. They must be a person open to innovation and new trends.
1. Understand and examine different data sources, as well as platforms and algorithms.
2. Development and maintenance of statistical models oriented to Credit Scoring, segmentation, fraud prevention, complying with the objectives set in terms of quality, cost, and time.
3. Design reports of different kinds adjusted to business needs.
4. Make proposals adapted to the needs of internal and/or external clients, meeting expectations to achieve the maximum level of satisfaction.
5. Execute already standardized processes, in addition to proposing new standards for the area in general.
6. Work with internal and external users to identify data needs and delivery mechanisms.
Qualifications
- Professional and postgraduate training: Professionals in Financial Engineering, Statistics, Mathematics, Economics, Systems Engineering.
- Technical knowledge: Programming languages: Python (essential), Spark (essential), SQL (essential), R (recommended), and Pandas (recommended).
- Intermediate English level.
- Time and priority management, Communication skills, Goal development and management, Desirable previous experience in Banking, Telecommunications or IT, Teamwork.
- More than 3 years of experience using the described technical requirements oriented to Analytics and/or Business Intelligence.
Additional Information
Our uniqueness is that we celebrate what makes us different. Experian's culture and people are key differentiators. We take our people agenda very seriously and focus on what really matters: DEI, work-life balance, development, authenticity, engagement, collaboration, well-being, reward and recognition, volunteering... and the list goes on. Experian's strong people-first approach has been recognized: Great Place To Work™ in 24 countries, FORTUNE Best Companies to work and Glassdoor Best Places to Work (globally 4.4 stars), to name a few. Take a look at Experian Life on social media or our careers site to understand why.
Experian is proud to be an equal opportunity and affirmative action employer. Innovation is a fundamental part of Experian's DNA and practices, and the diversity of our workforce drives our success. Everyone can succeed at Experian and bring their whole selves regardless of gender, ethnicity, religion, color, sexuality, physical ability, or age. If you have any disability or special needs that require accommodations, please let us know as soon as possible.
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